Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region Asian Disaster Preparedness Center/SERVIR-Mekong
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Anticipated Results Improved capacity of institutions to use earth observation information and geospatial information technologies Increased awareness by stakeholders of geospatial data, tools, knowledge products, and services Increased provision of user-tailored geospatial data, products, and tools to inform decision making ADPC strengthened as a regional provider of geospatial data analyses, and capacity building services
Product Description of RDCYIS The Regional Drought and Crop Yield Information System (RDCYIS) integrates drought monitoring and forecasting information as well as crop yield information that would allow decision makers in planning and preparedness during drought situations The system aims to help decision makers better prepare and respond towards droughts as well as helping the planning agencies and agricultural extension workers to disseminate drought related information to the farming communities creating awareness. As well as helping farming communities in considering various economic incentives, affordable coping strategies, and agricultural interventions coupled with social support services for the lower Mekong countries. Need assessments have been carried out based on country level consultations to identify end user needs. Consultations involved relevant government agencies and academic institutions 4
RHEAS RHEAS (Regional Hydrologic Extremes Assessment System) - A hydrologic now-cast and forecast framework - Developed by NASA Jet Propulsion Laboratory Hydrological Model VIC (Variable Infiltration Capacity model) RHEAS allows forecasts as well Crop Simulation Model DSSAT (Decision Support System for Agrotechnology Transfer) RHEAS makes traditionally un-spatial modelling systems to spatial Database PostGIS (Spatially enabled PostgresSQL) 4D Data Cube Approach
Nowcast & Forecast Configuration at SERVIR Mekong Assimilation and Ensembles are ON AS: Assimilation, SM: Soil moisture; BF: Base Flow; RO: Runoff; E: Evaporation; EB: Energy Balance; WB: Water Balance; ESP: Ensemble Streamflow Prediction; 7
Data Inputs Variable Dataset Tim. Cov. Temp. Res Spat. Res Spatial Coverage Table Mode Precipitation CHIRPS 1981- Daily 5km Global precip.chirps IN Precipitation TRMM 1998- Daily 0.25 o Global precip.trmm IN Precipitation RFE2 2001- Daily 0.10 o Africa precip.rfe2 IN Precipitation CMORPH 1998- Daily 0.25 o Global precip.cmorph IN Precipitation GPM 2014- Daily 0.10 o Global precip.gpm IN Temp/Wind NCEP 1981- Daily 1.875 o Global *.ncep IN Temp/Wind PRISM 1981- Daily 4km CONUS *.prism IN Soil moisture AMSR-E 2002-2011 Daily 0.25 o Global soilm.amsre AS Soil moisture SMOS 2009- Daily ~40km Global soilm.smos AS Soil moisture SMAP 2015- Daily 3/9km Global soilm.smap AS Evapotranspiration MOD16 2000-8 days 1km Global evap.modis AS Water storage GRACE 2002- Monthly 1.0 o Global tws.grace AS Snow cover MOD10 2001- Daily 1km Global snow.mod10 AS Snow cover MODSCAG 2001- Daily 1km Global snow.modscag AS Leaf Area Index MCD15 2002-8 days 1km Global lai.modis AS Meteorology IRI 2000- Monthly 2.5 o Global *.iri FC Meteorology NMME 2000- Daily 0.5 o Global *.nmme FC 8
Data Inputs Variable Dataset Tim. Cov. Temp. Res Spat. Res Spatial Coverage Table Mode Precipitation CHIRPS 1981- Daily 5km Global precip.chirps IN Temp/Wind NCEP 1981- Daily 1.875 o Global *.ncep IN Soil moisture SMOS/SMAP 2009- Daily ~40km Global soilm.smos AS Meteorology NMME 2000- Daily 0.5 o Global *.nmme FC 9
Nowcast Approach: Assimilation Assimilation is on SMOS SMAP AMSRE Sources for Observed SM Remotely sensed LAI ET SNOW Options for SM
Nowcast/Forecast Approach: Ensemble Runs (10 runs)
Nowcast/Forecast Approach Currently Being Used Nowcast - Continues run since 1981 in daily time scale ESP/Seasonal Forecast (iri/nmme) - (Ensemble Streamflow Prediction approach that resamples the climatology) - (resample climatologies based on the probabilities in IRI/NMME meteorological forcing) - Forecast for 90 days with 10 ensembles 12
Nowcast and Forecast Outputs Resolution of the output products is 25km Drought: SPI (1,3,6,12): Standardized Precipitation Index M SRI (1,3,6,12): Standardized Runoff Index H SMDI: Soil Moisture Deficit Index A Dry Spells: Number of dry spell events with at least 2-week duration A RZSM: Root Zone Soil Moisture A Drought Severity A Soil: Soil temperature for each soil layer (3 layers: 0-10cm, 10-40cm and 40-100cm) Soil total moisture content [mm] for each soil layer (3 layers: 0-10cm, 10-40cm and 40-100cm)
Nowcast and Forecast Outputs Resolution of the output products is 25km Water Balance: Baseflow Runoff Rainfall Total net evaporation Energy Balance: Surface temperature Net downward shortwave flux Net downward longwave flux Net upward latent heat flux Net upward sensible heat flux Net heat flux into ground
Drought Products (SPI and SRI) Forecast : January 2017 SPI SRI 15
Ensemble Drought Forecasts (SPI and SRI) Forecast situation in December 2016 Forecast situation during Dec Feb 2017 16
https://rdcyis-servir.adpc.net 17
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How to Improve RHEAS outputs 1. Bias correction of input data 2. Data assimilation [SM (SMOS, SMAP, AMSRE), LAI, ET, SNOW] 3. Ensemble runs [ex: 10/40 runs] 4. Calibration of VIC and DSSAT models 19
VIC Calibration Approach Calibration with streamflow (most common observation) and/or soil moisture and/or ET. VIC runoff baseflow Routing Model (RVIC) streamflow Verification with in-situ streamflow data and modify soil parameters Soil Parameters: most often adjusted during calibration of the VIC model include, b_infilt (parameter used to describe the Variable Infiltration Curve), Ds (represents the fraction of the Dsmax parameter at which non-linear base-flow occurs), Ws (fraction of maximum soil moisture where non-linear baseflow occurs), Dsmax (maximum velocity of baseflow for each grid cell) and soil depth. 20
Initiative of Faisal, Lee, et al, 2017 GSOD (Global Summary of the Day) by NCDC (National Climatic Data Center) via WMO Soil data from the Harmonized Land database (12.5km resolution) 21
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Clustering based on: Elevation Bulk Density % Clay (Top Clay) % Sand (Top Sand) Landuse LAI HWSD To effectively use the subset of calibrated VIC parameters, we need to identify optimal number of pedotransfer functions. The pedo-transfer functions are selected for this study that generally influence the evolution of calibrated VIC parameters related to above parameters. 24
Perform cluster analysis using the above mentioned pedo-transfer function to both Mekong River Basin area and the whole study area (LMR) to identify the areas that are similar in geophysical characteristics. RHEAS executed in open-loop Comparison of soil moisture products between RHEAS and SMAP/SMOS Expected correlation is about 75%. Procedure would be repeated (changing number of clusters) if the expected correlation gets less than 75%. 25
Comparison Results (2010-03) mm RHEAS SMOS Bias 3.19 RMSE 5.59 R (Correlation) 0.63 NSE (Nash Sutcliffe model efficiency coefficient) 0.40 26
Comparison Results (2015 and 2016): RHEAS SM and SMAP Month Correlation NSE Jan-2015 Feb-2015 Mar-2015 Apr-2015 0.79 0.5 May-2015 0.79 0.5 Jun-2015 0.75 0.4 Jul-2015 0.74 0.4 Aug-2015 0.74 0.4 Sep-2015 0.76 0.5 Oct-2015 0.79 0.5 Nov-2015 0.78 0.5 Dec-2015 0.80 0.6 Month Correlation NSE Jan-2016 0.78 0.5 Feb-2016 0.76 0.5 Mar-2016 0.81 0.6 Apr-2016 0.78 0.5 May-2016 0.79 0.5 Jun-2016 0.76 0.4 Jul-2016 0.75 0.4 Aug-2016 0.76 0.4 Sep-2016 0.77 0.5 Oct-2016 0.79 0.5 Nov-2016 0.79 0.5 Dec-2016 0.81 0.6 27
Simulating the Drought Event in 2015/16 NDJ-2015/16 JFM-2016 MAM-2016 SPI 3 months 28
Simulating the Drought Event in 2015/16 29
Simulating the Drought Event in 2015/16 NDJ-2015/16 JFM-2016 MAM-2016 SMDI 30
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Capacity Building on RHEAS Modeling Vietnam Academy of Water Resources (VAWR) 19-23 June and 2-6 Oct 2017 32
Co-development Engagements Vietnam Academy of Water Resources (VAWR): - Two pilot sites (Ninh Thuan and Binh Dinh provinces) for initial testing Reservoir Operation Tool (http://hochua.com/index.php#popup_tab-22) Mekong River Commission (MRC): - Providing all drought related products generated by RHEAS - Technical support for developing drought portal MRC Drought Portal 33
Future Developments Implement PostGIS database in Data Cube approach Generate time series graphs for user AOIs Add more statistics Include crop yield information for maize and rice crops Increase output data resolution to 5km Add customized and new indices/variables Include climate projections data Add Text bulletins 34
Let s Explore the Tool Now!!! https://servir.adpc.net https://rdcyis-servir.adpc.net 36